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Effect of Tibetan Plateau Orography Height Change on Stationary Disturbance Energy Conversion in East Asia
2020,25(4):345-352, DOI: 10.3878/j.issn.1006-9585.2019.19046
Abstract:Using the National Center for Atmospheric Research Community Atmosphere Model version 3 (CAM3) outputs and European Centre for Medium-Range Weather Forecasts Interim Reanalysis (ERA-Interim) data, the role of the orography of the Tibetan and Iranian Plateaus in modulating the sources of stationary wave energy is investigated in this study. The sources of stationary wave energy in the troposphere during winter are located in two areas, i.e., East Asia north of the plateau and western Pacific downstream of the plateau. When orographic uplift occurs, the baroclinic development weakens over East Asia north of the plateau and enhances over western Pacific downstream of the plateau in the troposphere. The location of the barotropic development of stationary wave energy is similar to that of baroclinic development. Meanwhile, the intensity of the barotropic development of stationary wave energy is weaker than that of baroclinic development in the troposphere. When orographic height uplift occurs, the barotropic development of stationary wave energy first weakens and then enhances over East Asia north of the plateau, whereas it enhances over Western Pacific downstream of the plateau in the troposphere. In the troposphere during winter, the total stationary wave energy development is consistent with the baroclinic development of stationary wave energy, which indicates that the baroclinic development of stationary wave energy plays an important role in the development of stationary wave.
2020,25(4):353-365, DOI: 10.3878/j.issn.1006-9585.2019.19052
Abstract:The MJO (Madden-Julian Oscillation) simulation ability of the numerical experiments from CNRM GCMs (General Circulation Models) participated in the MJOTF/GASS (MJO Task Force/Global Energy and Water Cycle Experiment Atmospheric System Study) project was evaluated by tracking the eastward propagating positive equatorial precipitation anomalies. The GCMs included a fully coupled simulation (CNRM-CM), a half-coupled simulation (CNRM-ACM), and an uncoupled simulation (CNRM-AM) based on 1991-2010 data. The possible impacts of air-sea coupling on the MJO simulation were investigated. The CNRM-CM showed the highest ability in simulating the MJO characteristics, in terms of the occurrence frequency, amplitude, and propagation range. The climatological sea surface temperature (SST) of the CNRM-CM and CNRM-ACM showed a distinct cold bias over the Indo-Pacific warm pool region, compared with that of the CNRM-AM. The cold bias did not strongly impact the MJO simulation ability compared with the impacts on the MJO simulation abilities of the CNRM-ACM and CNRM-AM. The zonal gradient of the intraseasonal SST was significant in the CNRM-CM, with a strong positive intraseasonal SST anomaly to the east of the MJO convection center and a negative intraseasonal SST anomaly to the west of the MJO convection center when the MJO was over the Indian Ocean. In contrast, such a gradient was lost in the CNRM-ACM and CNRM-AM. The results indicate that the impact of the air-sea coupling on the MJO simulations by the CNRM GCMs was mainly through the influences on the intraseasonal SST variability.
Spatial-Temporal Characteristics of the Emission Intensities of Several Major Greenhouse Gases and Aerosols under CMIP6 Scenarios
2020,25(4):366-384, DOI: 10.3878/j.issn.1006-9585.2020.20005
Abstract:Eight latest scenarios (SSPx-y scenarios), which are based on different shared socioeconomic paths (SSPs) are adopted in the Coupled Model Intercomparison Project Phase 6 (CMIP6) to project the probable magnitude and trend of future climate changes. In this article, the emission datasets of various major greenhouse gases and aerosols under the eight SSPx-y scenarios are analyzed, including emission intensities in the reference year (i.e., 2015), spatial and temporal variations of future emission intensities, and yearly change in emission intensities for the six typical selected sub-regions. Results show that the strongest emission intensities of carbon dioxide (CO2), methane (CH4), black carbon (BC), and sulfur dioxide (SO2) are distributed mainly in East and South Asia in 2015. In comparison with the reference year, variations in the intensities of CO2 and CH4 emissions in
2100show significant differences between the high and low radiative forcing scenarios. In addition, the average global emission intensities of BC and SO2 in 2100are weaker than those in the reference year under all scenarios. In terms of temporal variation, such as the development of bioenergy with carbon capture and storage (BECCS), the values of CO2 emission intensities in all sub-regions become negative in 2100for four low radiative forcing scenarios (i.e., radiative forcing values≤3.4 W/m2). On the other hand, the net intensity of negative emissions in South America is －0.3 kg m－2 a－1 under the SSP5-3.4 scenario in 2100, which is lower than that in all other sub-regions. Finally, a comparison of the variations in emission intensities in East and South Asia reveals that emission reduction actions in East Asia play a more effective role than those in South Asia in the future development described in all scenarios.
Statistical Features of Two Types of Mesoscale Convective Systems (MCSs) Generated over the Eastern Tibetan Plateau during 16 Consecutive Warm Seasons
2020,25(4):385-398, DOI: 10.3878/j.issn.1006-9585.2019.19040
Abstract:Two types of mesoscale convective systems (MCSs) generated over the eastern Tibetan Plateau (TP) during 16 consecutive warm seasons were identified and tracked by an automatic tracking algorithm based on hourly geostationary satellite TBB data that were provided by Kochi University. Following the manual verification of the automatic tracking results, statistical and comparative analyses of these two types of MCSs were conducted using NOAA’s CMORPH (Climate Prediction Center Morphing) precipitation data and NCEP’s CFSR (Climate Forecast System Reanalysis) reanalysis data. The main results show that July and August were the most active months regarding the MCSs’ generation over the eastern section of the plateau, but the percentages of MCSs’ vacating the TP of these two months were the lowest. In May, the number of MCSs generated reached a minimum, but up to nearly 40% of the MCSs could vacate the TP. The MCSs that could vacate the TP (V-MCS) usually showed a longer lifespan, earlier triggering time, and lower proportion of short lifespan cases, compared with the MCSs that could not vacate the TP (N-MCS). During the period of the research, the V-MCSs were usually faster in development and stronger in intensity, compared with the N-MCSs. However, owing to the much lower frequency in the occurrence of V-MCSs, their contribution to the local precipitation was only about 15%, which was approximately half the contribution of the N-MCSs. The composite circulation features of the V-MCSs and N-MCSs that were generated over the eastern plateau were significantly different. The shortwave trough and stronger westerly wind in the middle troposphere and the cyclonic wind shear in the lower troposphere provided more favorable conditions for the V-MCSs’ occurrence, maintenance, and eastward displacement. In contrast, divergence conditions in the upper troposphere were more conducive to the N-MCSs (the associated South Asia high in this type was stronger).
2020,25(4):399-409, DOI: 10.3878/j.issn.1006-9585.2019.19050
Abstract:Wetlands play important roles regulating the local microclimate. Studying the characteristics of wetland microclimate effects can help to specifically understand the impact of the wetlands on the local microclimate. In this study, we chose Hengshui Lake in Hengshui City, Hebei Province, as the study area and analyzed the microclimate effects of Hengshui Lake during different seasons by comparing the meteorological elements inside and outside the lake. The data came from 11 conventional meteorological stations in Hengshui City. The results show that: (1) Hengshui Lake has a remarkable cold island effect, wet island effect, and a wind island effect, which modify the surrounding climate characteristics. (2) The microclimate effect of Hengshui Lake has an obvious seasonal characteristic. The order of the average cold island effect during the four seasons is spring > winter > autumn > summer; the order of the wet island effect is summer > spring > autumn > winter; and the order of the wind island effect is spring > summer > winter > autumn. The microclimate effect is intense in spring. (3) Hengshui Lake shows an obvious circadian rhythm in its microclimate effect. The cold island effect is stronger at night than during the day, while the wet island and wind island effects are stronger during the day than at night.
Improvement of the Snow-Depth Retrieval Algorithm Using Passive Microwave Remote Sensing over the Arxan Region Inner Mongolia
2020,25(4):410-418, DOI: 10.3878/j.issn.1006-9585.2019.19038
Abstract:Long-term snow-depth observations at Arxan station are used to evaluate the application of snow-depth products retrieved from the AMSR-E and AMSR-2 microwave data and Chinese snow-depth dataset developed by Chinese researchers and to establish a new snow-depth retrieval algorithm. The statistical snow-cover days and maximum snow-depth records derived from the 35-year Chinese snow-depth dataset and station observations are consistent, particularly after 2000. The snow-depth variation trend estimated from the snow-depth products retrieved from the AMSR-E and AMSR-2 microwave data is consistent with that retrieved from the station observations, with the correlation coefficient greater than 0.6. However, the variation range of the snow-depth products is wider than that of the station observations. Thus, the root mean square error (RMSE) of both snow-depth datasets is high (i.e., approximately 13 cm). The Chinese snow-depth dataset at Arxan station shows a higher correlation coefficient of 0.65 and a lower RMSE of 6.3 cm than the station observations. To better estimate snow depth in the Arxan region, a new snow-depth retrieval method is developed using both space-borne passive microwave brightness temperature and observed snow-depth data at Arxan station. The validation shows that the snow-depth data retrieved using the new method has a higher correlation with the observations (i.e., approximately 0.77) and a lower RMSE (i.e., approximately 4.68 cm) than the snow-depth products retrieved from the AMSR-E and AMSR-2 microwave data and Chinese snow-depth dataset used in this study.
2020,25(4):419-428, DOI: 10.3878/j.issn.1006-9585.2020.19061
Abstract:To apply Holroyd’s proposed cloud particle habit classification method to the ice particle measured by airborne cloud imaging probe (CIP) in northern China, this article improves the thresholds in the Holroyd’s cloud particle habit classification based on historical airborne measurement data, which makes the habit classification method more suitable for the ice particle measured by CIP in northern China. The improved threshold method is used to process and analyze the airborne measurement data from a precipitation stratus cloud in Shanxi Province. It is found that there are four types of ice particles with a frequency of occurrence greater than 15% in the vertical and horizontal distribution in this stratiform precipitation cloud; three among them are relatively fixed, namely, graupel, line shape, and irregular type. The fourth type is related to the specific cloud environment. In the vertical direction, it is dendrite (-8 to 0℃) or tiny (-12 to 8℃), and in the horizontal direction of different heights it is dendrite (
5200m) or tiny ( 5500m) or plate ( 5800m). The concentration of ice particles fluctuates widely in the horizontal and vertical distribution, with a minimum of less than 1 L-1 and a maximum of more than 25 L-1. The maximum values in the vertical distribution are located in the central and lower parts of the cloud. The ice water content in the cloud also fluctuates a lot in the horizontal and vertical direction. The maximum vertical value area in the cloud is basically consistent with the number concentration of ice particles.
Characteristics and Cause Analyses of Arctic Oscillation Variability during the Typical Periods in Last Millennium Based on PMIP3 and CMIP5 Simulations
2020,25(4):429-442, DOI: 10.3878/j.issn.1006-9585.2020.20011
Abstract:The variability and corresponding mechanisms of the Arctic Oscillation (AO) during three typical periods, the Medieval Climate Anomaly (MCA), Little Ice Age (LIA), and Present Warm Period (PWP), in the last millennium were analyzed using simulations from nine Earth system models (ESMs) from the Paleoclimate Modeling Intercomparison Project Phase III (PMIP3) Last Millennium experiment and Paleoclimate Model Intercomparison Project Phase 5 (CMIP5) historical experiments. Compared with the NCEP reanalysis data, the ESMs reasonably reproduce the AO spatial pattern and inter-annual period, and most ESMs reproduce the AO strengthening trend in the last five decades. Simulations show that there is no consistent AO phase during the MCA among the different models. The eight models simulated generally negative AO phases during the LIA and positive phases during the PWP. These simulated results are consistent with previous studies using proxy reconstructions and observations. The multi-model ensemble mean indicates that there is no significant sea level pressure (SLP) change over the Arctic region during the MCA. The SLP anomalies over the Arctic region are significantly positive during the LIA and significantly negative during the PWP. These changes in SLP are related to the anomalous lower temperature during the LIA and higher temperature during the PWP over the Arctic region. Our study suggests that the AO variability during the LIA and PWP are influenced by the natural and anthropocentric forcing, respectively.
Influence of Land Use Data Optimization Schemes on WRF Model Simulations of High Temperature Processes in Shanghai
2020,25(4):443-456, DOI: 10.3878/j.issn.1006-9585.2020.20013
Abstract:The default land use data used in the Weather Research and Forecasting Model (WRF) differ significantly from the actual land use situation, which affects the simulation results. For this reason, many researchers have proposed schemes for updating land use data prior to running the model. The simplest method involved correcting the size of the urban area. Due to the heterogeneity of the urban surface, it has been suggested that the urban landscape be subdivided into refined classification areas. However, in the literature on the impact of land use data on the WRF model, most studies have only compared the simulation results before and after data updating, and have not distinguished the two factors of changes in the urban areas and urban heterogeneity. In this paper, the authors consider the use of urban area correction and refined classification synthetically. In the area correction scheme and the two refined classification schemes, three kinds of optimized land use data are generated. Combined with default land use data, the authors established four cases to simulate two high temperature weather processes that occurred in August 2018 and August 2019 in Shanghai. The results of these two simulations are: 1) The simulation results for temperature, relative humidity, and wind speed were improved after the land use data in the WRF model had been updated. 2) The size of an urban area is the most critical factor affecting the temperature. The area correction reduces reduced the average root mean square error (RMSE) by 0.86℃, but the refined classification reduced the average RMSE by just 0.04℃ at most. 3) The refined classification method primarily affected the wind speed and relative humidity. Although area correction reduced the average RMSE of wind speed by just 0.04 m/s, the refined classification method further reduced the RMSE by up to 0.19 m/s. The mean RMSE of relative humidity was reduced by just 0.23% by area correction, while the maximum RMSE was reduced by 2.25% by refined classification. 4) Generally speaking, to some extent, the heterogeneity of a city is considered in refined classification schemes, so the simulation results for temperature, relative humidity, and wind speed are improved to a greater extent, and the more detailed is the classification, the better is the effect.
Volume 25,2020 Issue 4
Linear trends in high temperature and heatwave occurrence in China for the period 1960~2018: analysis method and results
Available online:January 19, 2020 DOI: 10.3878/j.issn.1006-9585.2019.19134
Abstract:High temperature and heatwave (HT and HW) directly impact human health and crop growth. Investigating the trends in the occurrence of HT and HW is one of the fundamental questions of climate change research and can provide valuable information for living and production. Most of the previous studies on trends in the occurrence of HT and HW used ordinary least squares (OLS) method to calculate the magnitude of linear trend and then used student’s t-test to determine the statistical significance of this trend. This study examined whether traditional methods are suitable for the trend estimation of the occurrence of HT and HW in China. By showing a case of the annual count of HT days with extremely excessive occurrences in 2018 at a station in northeastern China, we illustrated that OLS method is sensitive to outliers and can give spurious trend. Further, through normality testing and autocorrelation calculation, we found at least 91.14% of stations and 90.06% of grid boxes for the annual count of HT days and 92.18% of stations and 87.74% of grid boxes for the annual count of HW in China are non-Gaussian, and the majority of them have serial correlation. Applying a nonparametric method that is insensitive to outliers and takes into account serial correlation, we gave a more accurate estimation of the linear trends in the annual count of HT days and HW for every station and grid box, four typical regions average, and China area-average for the period 1960~2018. The results show that stations with statistically significant increasing trend in HT days occurred mainly in South China and northwestern China, and those in HW occurred nearly only in South China and several stations in Xinjiang Autonomous Region. In terms of area average of the trend in annual count of HT days and HW, only South China region and northwestern China region show statistically significant increasing trend, whereas North China and northeastern China not significant; those of China average are both significant. This study provides referential information for the choice of method in the estimation of trend and its statistical significance and in statistical prediction for HT days and HW.
Multi-timescale features for surface air temperature in the source region of the Yellow River during 1953-2017
Available online:November 05, 2019 DOI: 10.3878/j.issn.1006-9585.2019.19026
Abstract:Abstract: Based on the annual averaged surface air temperature data from eight meteorological stations in the source region of the Yellow River using the Ensemble Empirical Mode Decomposition (EEMD) approach, the multi-timescale temperature features of meteorological stations with Madoi as a representative during 1953-2017 and their contributions to the temperature variations are revealed. The correlations between different time-scale temperature oscillations with the SST indices are analyzed, particularly with the Atlantic Multidecadal Oscillation (AMO). The results demonstrated that: (1) a long-term temperature trend was 0.31℃/10a during 1953-2017 in the source region of the Yellow River, and the warming started in the late 1980s and accelerated in the late 1990s. (2) There were 3-year, 6-year, 11-year, 25-year, 64-year and 65-year quasi-cycle oscillations for the temperature during 1953-2017. Among them, the 3-year and 65-year quasi-cycle oscillations were significant. The amplitude of 3-year time-scale oscillation was large before the 21st century and decreased after the 21st century, while the amplitude of 65-year oscillation was enhanced after the 21st century. (3) The 3-year quasi-cycle oscillation occupied a dominant position during the period of 1953-1997, and the contribution of 65-year oscillation increased nearly five times which was equivalent to the contribution of the 3-year oscillation during the rapid warming period since 1998. (4) The correlations between temperature with Nino3.4 and PDO indices were not significant, but the maximum significant correlation was found when the temperature led PDO 22 years. Unlike PDO, the maximum significant correlation was found when AMO led the original temperature and its three inter-decadal components 0 and 3-7 years which supported that AMO had a significant impact on the temperature variation in the source region of the Yellow River. (5) The positive warm phase of AMO corresponded to the warming of the East Asia including China, and the source region of the Yellow River was only a part of that area. The negative cold phase of AMO from the early 1960s to the middle and late 1990s and the positive warm phase of AMO from the early 1990s to the present corresponded to the negative and positive phases of the temperature in the source region of the Yellow River. The AMO highly correlated with the 65-year oscillation. These results supported that AMO was an important climatic oscillation affecting the temperature variation especially on the inter-decadal time scales in the source region of the Yellow River.
Development of a Meteorology-Chemistry Two-Way Coupled Numerical Model (WRF-NAQPMS) and Its Application in a Severe Autumn Haze Simulation over the Beijing-Tianjin-Hebei Area, China
2014,19(2):153-163, DOI: 10.3878/j.issn.1006-9585.2014.13231
Abstract:An aerosol-optical module based on Mie scattering theory has been implemented in the Nested Air Quality Prediction Modeling System (NAQPMS), and a new coupler has been developed to deal with the interaction between the mesoscale meteorology model WRF (Weather Research and Forecasting Model) and NAQPMS. The one-way off-line and two-way coupled WRF-NAQPMS models are compared to simulate the severe haze in the Beijing-Tianjin-Hebei area from 27 September to 1 October 2013. The results show that the simulated meteorological elements and PM2.5 concentrations from the two-way coupled model with the aerosol direct radiation effect are more consistent with observations. During the haze period, the boundary layer meteorological elements change significantly because of the aerosol direct radiation effect over the Beijing-Tianjin-Hebei area: Incoming solar radiation is reduced by 25%, the 2-m temperature decreases by 1 ℃, the turbulent kinetic energy is reduced by 25%, the 10-m wind speed decreases by up to 0.2 m/s, and the planetary boundary layer (PBL) height is reduced by 25%. These changes make the atmospheric boundary layer more stable and further exacerbate air pollution over the areas where it is already severe, for example, the PM2.5 concentration increases by up to 30% over Shijiazhuang City. The analysis indicates that there is a positive feedback mechanism between haze and boundary layer meteorology, and the two-way coupled model incorporating this feedback is helpful for accurate simulation and forecasting of haze pollution processes.
2008,13(2):123-134, DOI: 10.3878/j.issn.1006-9585.2008.02.02
2010,15(4):337-353, DOI: 10.3878/j.issn.1006-9585.2010.04.01
Variations of the Sea Surface Temperature in the Offshore Area of China and Their Relationship with the East Asian Monsoon under the Global Warming
2011,16(1):94-104, DOI: 10.3878/j.issn.1006-9585.2011.01.09
Abstract:Based on the long time series of mean Sea Surface Temperature (SST) and high-resolution wind field reanalysis data such as HadISST and ERA-40 reanalysis data, the variations of the SST in the offshore area of China and their relationship with the East Asian Monsoon (EAM) in winter (December to the next February) and summer (June to August) are analyzed using the Empirical Orthogonal Function (EOF) and linear regression analysis methods. The results show that: 1) The SST in the offshore area of China in winter or summer exhibited significant interannual and interdecadal variations, and experienced a climate shift in the mid-1980s. The areas with the strongest increase in SST are located in the East China Sea (ECS) in winter and in the Yellow Sea in summer. The SST increased by 1.96°C in winter for the period of 1955-2005 and 1.10 °C in summer for the period of 1971-2006. 2）The EAM has displayed distinct interannual and interdecadal variations with a weakening trend since the end of the 1980s in winter, and since the end of the 1970s in summer. In addition, the linear regression analysis indicates the relationship of the SST to EAM in winter on interdecadal timescale is closer than that on interannual timescale. The interdecadal weakening trend of EAM in winter contributes to the rise in SST in the offshore areas of China, particularly significant in the ECS. Moreover, the related areas of winter or summer mean SST on the interannual timescale in the offshore area of China to the EAM are located in the South China Sea (SCS), and the relationship in winter is much more obvious than that in summer. It is found that the interannual variation of SST in the SCS has obvious relation to the anomalies of the meridional southward and northward winds over the SCS and zonal migration of the subtropical anticyclone over the western Pacific.
2006,11(1):14-32, DOI: 10.3878/j.issn.1006-9585.2006.01.02
2011,16(6):733-741, DOI: 10.3878/j.issn.1006-9585.2011.06.07
Abstract:A field performance of Doppler wind lidar Windcube (released by Leosphere Company) was conducted by Institute of Atmospheric Physics, Chinese Academy of Sciences (IAP/CAS) and Leosphere Company (from France) at the 325 m meteorological tower site (a part of IAP, located between 3rd North Ring Road and 4th North Ring Road) from 11 December to 14 December 2007. The intercomparison of wind speed and wind direction obtained by Windcube and wind cup anemometers (fixed in the meteorological tower) shows that：1) 10 min averaged wind speed is highly consistent between two types of wind data at six matched levels (63 m, 80 m, 100 m, 120 m, 160 m, and 200 m), the correlation coefficients all equal or exceed 0.98. 2) 10 min averaged wind direction is calculated with the vector method, the correlation coefficients of averaged wind direction at the six levels are 0.99. 3) In comparison with domestic Doppler wind lidar, Windcube performs slightly better in wind speed measuring, and equally well in wind direction measuring. The intercomparison indicates that Windcube is a reliable and swift mobile system mea suring wind profile at low levels.
2009,14(1):69-76, DOI: 10.3878/j.issn.1006-9585.2009.01.08
Abstract:作为酸雨和细粒子的前体物，SO2对空气质量和人体健康乃至气候与环境的影响十分重要，特别是在不利于扩散的气象条件下，SO2可造成城市短时间严重污染事件。作者以2006年北京325 m气象塔15 m观测平台SO2观测数据为基础，结合同步气象资料分析研究发现：1) SO2浓度冬季高、夏季低；全年日均值为(22.5±22.1)×10-9，最大日均值能达到113×10-9。日变化呈现双峰型，峰值出现在北京时间08:00和22:00；并且季节差异明显，冬季浓度为夏季的4.5倍，采暖期为非采暖期的3.2倍。2) 风向、风速与SO2扩散和输送密切相关，高浓度SO2在东北、东、西方向上出现频率分别为25.8%、13.8%和11.8%；而西北、北方向上的风速越大对SO2清除效果越好。3)利用平均晴空指数划分采暖期阴霾天和晴天，发现阴霾天混合层高度与平均风速仅为(376±204) m和1.1 m·s-1，容易造成SO2累积。4) SO2污染过程呈现周期性的局地累积—清除特征，地形、静风和暖低压是造成北京2006年1月一次重污染事件的成因。
The Mutual Response between Dynamical Core and Physical Parameterizations in Atmospheric General Circulation Models
2011,16(1):15-30, DOI: 10.3878/j.issn.1006-9585.2011.01.02
Abstract:A study of the interaction and mutual response between dynamical core and physical parameterizations by atmospheric general circulation models CAM3.1 and IAP AGCM4.0 is presented. Both the two models were integrated 60 d with ideal physics (Held-Suarez forcing) and with full physical package, respectively. The results show that the mutual responses between dynamical core and physical parameterizations are very different in the troposphere at low latitudes and high latitudes. In the tropical troposphere, the variability of temperature tendency due to dynamical core and that due to physical parameterizations are both large and have significant contributions to the variability of total temperature tendency, and they are in inverse correlation to compensate each other. In the polar middle and upper troposphere, the variability of total temperature tendency mainly relies on the tendency due to dynamical core, while the variation of temperature tendency due to physics is very slow, which can be seen as a stationary forcing. Unlike the tropical regions, there is a positive correlation between the temperature tendency due to dynamics and that due to physics in Polar regions. Moreover, the interactions and mutual responses between the individual physical parameterizations are also analyzed. The results show that the variation of temperature tendency due to moist process is the largest of all the physical parameterizations, and it contributes most to the total temperature tendency due to physics. The variation of temperature tendency due to long wave radiation is also large at high latitudes, while the variation of temperature tendency due to short wave radiation and that due to vertical diffusion are relatively small. There is a negative feedback between the cooling rate of long wave radiation and the heating rate of short wave radiation.
1999,4(1):98-103, DOI: 10.3878/j.issn.1006-9585.1999.01.21
2004,9(2):278-294, DOI: 10.3878/j.issn.1006-9585.2004.02.05
A Comparison of NCEP/NCAR, ERA-40 Reanalysis and Observational Data of Sensible Heat in Northwest China
2009,14(1):9-20, DOI: 10.3878/j.issn.1006-9585.2009.01.02
Simulation of Potential Vegetation Distribution and Estimation of Carbon Flux in China from 1981 to 1998 with LPJ Dynamic Global Vegetation Model
Abstract:The LPJ DGVM (Lund Potsdam Jena Dynamic Global Vegetation Model), which is a process based model, is used to simulate the vegetation distribution and estimate the interannual variation of net primary production (NPP), heterotrophic respiration (Rh) and net ecosystem production (NEP)in China from 1981 to 1998. It is shown that there are six main plant functional types (PFTs) besides the desert,that is tropical broadleaved evergreen tree, temperate broadleaved evergreen tree, temperate broadleaved summergreen tree, boreal needleleaved evergreen tree, boreal needleleaved summergreen tree and C3 perennial grass. In China, the total NPP varies between 2.91 Gt·a-1(C) (1982) and 3.37 Gt·a-1(C) (1990), increases by 0.025 Gt (C) average per year and has an increasing trend of 0.96%. The total Rh varies between 2.59 Gt·a-1(C) (1986) and 319 Gt·a-1(C)(1998), grows by 1.05% per year and by 0.025 Gt(C) per year. The linear trend of NPP and Rh for C3 perennial grass is more remarkable than those for other PFTs. The simulation of NEP is reasonable when the fire is brought in the model. Annual total NEP varies between -0.06 Gt·a-1(C)(1998)and 0.34 Gt·a-1(C)(1992). It is demonstrated that the terrestrial ecosystem is carbon sink in China. The above results are similar to those simulated by other models.
Variation Characteristics of the Sunshine Duration and Its Relationships with Temperature，Wind Speed，and Precipitation over Recent 59 Years in China
2011,16(3):389-398, DOI: 10.3878/j.issn.1006-9585.2011.03.14
Abstract:Using the data of sunshine duration, temperature, wind speed， and precipitation from 194 basic/reference stations over China from 1951 to 2009, according to the climatic division, the whole domain of China is classified into 11 climatic regions. The authors studied the changes in annual and seasonal trends of the sunshine duration by using linear trend analysis and Morlet wavelet analysis, and analyzed the characteristics between the sunshine duration and the temperature, the wind speed, and the precipitation. It was found that the annual sunshine duration showed a significant decreasing tendency during the recent 59 years with a decreasing rate of 36.9 h·(10 a)-1. The trend variations of the annual sunshine duration in 11 climatic regions were similar with that in the whole nation, only had the difference in degree. The sunshine duration of China changed from intensive to weak in 1981. There is an obvious 7－10-year periodic oscillation for the annual sunshine duration of China before the mid 1990s. The sunshine duration of the four seasons had a bigger decreasing amplitude in the coastal areas than in the inland areas, and in the South than in the North. There was a negative correlation between the annual sunshine duration and the temperature (correlation coefficient is -0.52), but a positive correlation between the annual sunshine duration and the wind speed (correlation coefficient is 0.76), and a negative correlation between the annual sunshine duration and the precipitation (correlation coefficient is -0.27). The first two correlation coefficients and the last correlation coefficient passed 99.9% and 95% confidence levels，respectively.
Cause and Anomalous Characteristics of the South China Sea Monsoon Trough Producing Heavy Rainfall in South China
2011,16(1):1-14, DOI: 10.3878/j.issn.1006-9585.2011.01.01
Abstract:Atmospheric processes associated with the South China Sea (SCS) monsoon trough which caused the heavy rainfall in pentad 3 of August 2007 in South China are analyzed using the reanalysis data of NCEP and satellite images. The results indicate that the Asian summer monsoon trough has independent space structure, convergence in the low layers and divergence in the high layers are in the south of the Asian summer monsoon trough. The climate analysis shows that both the Indian monsoon trough and the SCS monsoon trough reach their maximum in 〖JP2〗August. The SCS monsoon trough in pentad 3 of August 2007 was located in South China coastal areas and had strong intensity. The convergence in the low layers and divergence in the high layers were also stronger. The Indian monsoon trough was also stronger. The strengthened South Asian high locating over the Tibetan Plateau is the main cause for the strengthening of the Asian monsoon trough. The subtropical high in the western Pacific is located over Japan and is intensified, which is propitous to the northward 〖JP〗movement and the enhancing of the SCS monsoon and monsoon trough. The increased temperature over the Tibetan Plateau induces the stronger easterly in the upper levels, westerly in the low levels,and the enhancing convergence in the low layers and divergence in the high layers of the SCS monsoon trough. The long wave trough in the westerly belt is intensified and extends to Southwest China, which causes the SCS monsoon trough to become stronger. The SCS monsoon trough has an intraseasonal period. The intraseasonal oscillation has an important effect on the northward movement and enhancement of the SCS summer monsoon trough.
2011,16(1):47-59, DOI: 10.3878/j.issn.1006-9585.2011.01.05
Abstract:Based on the MODIS observations, the performance of Interactive Canopy Model(ICM), a dynamic vegetation model including the carbon and nitrogen cycles of the terrestrial ecosystem, has been assessed. The Leaf Area Index (LAI), a key parameter with seasonal variation in vegetation dynamics, is simulated by ICM and compared with the MODIS data. The results show that ICM can simulate the main characteristics of the seasonal LAI fluctuations. Compared to the observation, LAI is overestimated in high and low latitudes, but underestimated in middle latitudes by the model. The underestimation of the LAI in middle latitudes is followed by the vegetation sprout for the reason that the modeled growth is always slower than the observed one. The bimodal distributions for the tropical evergreen broadleaf trees and crops have not been well captured. In addition, the simulated results for the grassland are more reasonable than other Plant Function Types (PFTs). The results will provide important clues for the parameterization improvement and parameters optimization of the ICM.
2008,13(1):75-83, DOI: 10.3878/j.issn.1006-9585.2008.01.10
Combination of Wavelet Decomposition and Least Square Support Vector Machine to Forcast Atmospheric Ozone Content Time Series
2010,15(3):295-302, DOI: 10.3878/j.issn.1006-9585.2010.03.09
Abstract:The atmosphere ozone content forecast model was established based on the combination of wavelet decomposition and advanced Least Square Support Vector Machine (LSSVM) regression. This can be approached in three steps: (1)The observations were decomposed into several different frequency signal subsets,(2)the independent prediction models of decomposed signals with Takens delay embedding theorem and Least-Squares Support Vector Machine (LSSVM) were set up, (3)independent predicted results were integrated as the final prediction with wavelet reconstruction. Application experiments with data from Xianghe and the other three observation stations show that the method can make better prediction effectively for the atmospheric ozone content, as compared with conventional Support Vector Machine(SVM) and Artificial Neural Network(ANN).
A Research on the Application of Spatial Difference Method in Quality Control of Surface Meteorological Data
2010,15(3):229-236, DOI: 10.3878/j.issn.1006-9585.2010.03.02
Abstract:A new Quality Control（QC）technique called spatial difference method is introduced in detail and applied to spatial checking of some basic meteorological elements at seven representative stations in China for the year of 2007 in order to evaluate the applicability of this approach．The checking tests are conducted on ten basic meteorological elements including daily mean pressure，maximum pressure，minimum pressure，mean temperature，maximum temperature，minimum temperature，mean vapor pressure，mean surface temperature, maximum surface temperature, and minimum surface temperature．It is shown that this method works well in identifying errors of single meteorological element．As compared with spatial regression test on discriminating artificial errors，the spatial difference method is more effective．Furthermore，same as the other spatial checking methods，the distribution of neighboring weather stations should be concerned necessarily as influence factors．
2002,7(2):209-219, DOI: 10.3878/j.issn.1006-9585.2002.02.08
2010,15(5):541-550, DOI: 10.3878/j.issn.1006-9585.2010.05.02
Abstract:The Nested Air Quality Prediction Modeling System (NAQPMS) has been applied to the routine air quality forecast in Beijing during the Olympic Games. Monte Carlo method is used to analyze the uncertainty of ozone simulation of NAQPMS during the Olympic Games, from 8 to 24 Aug 2008. Latin hypercube sampling has been used for multi-variables sampling, and 50 ensemble runs have been made with 154 parameter uncertainties being considered together. By the temporal average, the most important parameter to the surface ozone output uncertainty in Beijing is the local precursor emissions during the day time. Other important factors include NO2 photolysis coefficient, wind direction, precursor emissions from the surrounding areas of Beijing, and vertical diffusion coefficient. The wind direction and precursor emissions from the surrounding areas of Beijing have the greatest impact on the uncertainty of daytime ozone simulation at higher levels (above about 150 m). The main uncertainty factors in ozone simulation at night are local NOx emissions and vertical diffusion coefficient. Given the predefined input uncertainties, the average uncertainty of ozone simulation is 19 ppb, ranging from 2 ppb to 49 ppb.
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Editor in chief: 李崇银